Relationship and Differential Validity of Alexithymia and Depression: A Comparison of the Toronto Alexithymia and Self-Rating Depression Scales
Bibliographic record
Abstract
Theoretically, the constructs of alexithymia and depression share many common characteristics. Empirically moderate correlations between measures of alexithymia and depression have been found, hence it has been argued that the Toronto Alexithymia Scale (TAS) may be, at least in some part, just another measure for depression. The purpose of this study was to evaluate the construct validity of alexithymia and to analyze the relationship between alexithymia and depression. Exploratory and confirmatory factor analyses were conducted on the combined items of the TAS-20 and the Self-Rating Depression Scale (SDS) in a psychosomatic and alcoholic inpatient sample (n = 199) and a sample of normal adults (controls, n = 174). The exploratory factor analysis in the patient sample yielded a 4-factor structure. Within each factor there was no overlap between the items of the TAS-20 and the SDS. Two factors were comprised of items of the TAS-20 and two factors consisted of items of the SDS. This 4-factor model also showed an acceptable fit for the data of the normal sample in a confirmatory factor analysis. Moderate correlations between the TAS- 20 and SDS total scores and some factors were found. Both instruments, the TAS-20 and the SDS, seem to measure distinct constructs and are not just different measures for the same underlying construct. This provides support for the differential validity of the alexithymia and depression constructs and is in accordance with previous findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".